Estimation of Gridded Population with Spatial Downscaling in South Korea
Sungdon Kim,
Youngmi Lee and
Haejune Oh ()
Additional contact information
Sungdon Kim: Department of Information and Statistics, Gyeongsang National University, Jinju 52828, Republic of Korea
Youngmi Lee: Department of Statistics and Research Institute of Applied Statistics, Jeonbuk National University, Jeonju 54896, Republic of Korea
Haejune Oh: Department of Information and Statistics, Gyeongsang National University, Jinju 52828, Republic of Korea
Sustainability, 2025, vol. 17, issue 4, 1-26
Abstract:
South Korea faces serious challenges regarding population imbalance and sustainability due to low birth rates and the aging population. This study utilizes future population projection scenarios provided by Statistics Korea to estimate population distributions at both regional and grid levels. The analysis applies an urban growth model for administrative divisions and a modified gravity model for grid-level estimations. The modified gravity model enhances the prediction accuracy by effectively accounting for multi-centered urban structures and excluding non-residential areas such as mountains, rivers, and parks. Additionally, a novel spatial weight matrix considering train station connectivity is introduced. The results show that incorporating public transportation infrastructure around cities slows the rate of population decline, highlighting its mitigating effects on regional extinction. The study predicts that over 30 cities will face depopulation risks by 2072, while population concentration in the Seoul metropolitan area will persist. The grid-level analysis reveals detailed patterns of population imbalance within regions, particularly identifying uninhabited areas and their spatial distribution. These findings carry significant implications for infrastructure planning and regional development. By employing innovative modeling approaches and high-resolution projections, this study provides policymakers with valuable insights into South Korea’s demographic challenges and potential advances in sustainable urban and regional development.
Keywords: population; downscale; future population scenario; city growth model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2071-1050/17/4/1511/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/4/1511/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:4:p:1511-:d:1589486
Access Statistics for this article
Sustainability is currently edited by Ms. Alexandra Wu
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().